A new study by Terasaki et al. highlights the role of physical forces in biological form by showing that connections between stacked endoplasmic reticulum cisternae have a shape well known in classical differential geometry, the helicoid, and that this shape is a predictable consequence of membrane physics.
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| http://dx.doi.org/10.1016/j.cell.2013.06.032 | DOI Listing |
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Integrating deep learning and machine learning for improved CKD-related cortical bone assessment in HRpQCT images: A pilot study.
Bone Rep
March 2025
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States of America.
High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. This proof-of-concept study merges deep learning and machine learning to 1) improve automatic segmentation, particularly in cases with severe cortical porosity and trabeculated endosteal surfaces, and 2) maximize image information using machine learning feature extraction to classify CKD-related skeletal abnormalities, surpassing conventional DXA and CT measures. We included 30 individuals (20 non-CKD, 10 stage 3 to 5D CKD) who underwent HRpQCT of the distal and diaphyseal radius and tibia and contributed data to develop and validate four different AI models for each anatomical site.
View Article and Find Full Text PDFUnlabelled: Ultrasound imaging plays an important role in the early detection and management of breast cancer. This study aimed to evaluate the imaging performance of a range of clinically-used breast ultrasound systems using a set of novel spherical lesion contrast-detail (C-D) and anechoic-target (A-T) phantoms.
Methods: C-D and A-T phantoms were imaged using a range of clinical breast ultrasound systems and imaging modes.
Mechanisms of the Photomechanical Response in Thin-Film Dye-Doped Glassy Polymers.
Polymers (Basel)
January 2025
Department of Physics, Washington State University, Pullman, WA 99163, USA.
This work aims to determine the mechanism of the photomechanical response of poly(Methyl methacrylate) polymer doped with the photo-isomerizable dye Disperse Red 1 using the non-isomerizable dye Disperse Orange 11 as a control to isolate photoisomerization. Samples are free-standing thin films with thickness that is small compared with the optical skin depth to assure uniform illumination and photomechanical response throughout their volume, which differentiates these studies from most others. Polarization-dependent measurements of the photomechanical stress response are used to deconvolute the contributions of angular hole burning, molecular reorientation and photothermal heating.
View Article and Find Full Text PDFDifferentiating Apical and Basal Left Ventricular Aneurysms Using Sphericity Index: A Clinical Study.
Medicina (Kaunas)
January 2025
Cardiovascular Institute ''Dedinje'', 11040 Belgrade, Serbia.
: Left ventricular aneurysm (LVA) causes geometric changes, including reduced systolic function and a more spherical shape, which is quantified by the sphericity index (SI), the ratio of the short to long axis in the apical four-chamber view. This study aimed to assess SI's value in A-LVA and B-LVA, identify influencing factors, and evaluate its clinical relevance. : This clinical study included 54 patients with post-infarction LVA and used echocardiography to determine LVA locations (A-LVA near the apex and B-LVA in the basal segments), with SI and other echocardiographic measures assessed in both systole and diastole for the entire cohort and stratified by A-LVA and B-LVA groups.
View Article and Find Full Text PDFInformation Geometry and Manifold Learning: A Novel Framework for Analyzing Alzheimer's Disease MRI Data.
Diagnostics (Basel)
January 2025
Preclinical Department, Faculty of Medicine, Lucian Blaga University of Sibiu, 550024 Sibiu, Romania.
: Alzheimer's disease is a progressive neurological condition marked by a decline in cognitive abilities. Early diagnosis is crucial but challenging due to overlapping symptoms among impairment stages, necessitating non-invasive, reliable diagnostic tools. : We applied information geometry and manifold learning to analyze grayscale MRI scans classified into No Impairment, Very Mild, Mild, and Moderate Impairment.
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